Continue WEMD Simulation Guided by CryoEM Maps
Category Paths
Follow one of these paths in the Orion user interface, to find the floe.
Role-based/Structural Biologist
Solution-based/Target Identification/Target Preparation
Task-based/Target Prep & Analysis/Protein Preparation
Product-based/Molecular Dynamics/WESTPA
Description
This floe continues a previous WEMD simulation for sampling the diverse conformational states of a protein guided by different types of cryo-EM maps. Generally, this floe is used to perform long WEMD simulations using more advanced options or to continue a simulation that was stopped unexpectedly. Namely, this floe can be used to continue simulations from these automated floes: Automated WEMD Simulation and Best Structure Search Guided by Target Cryo-EM Map and Automated WEMD Simulation and Best Structure Search Guided By Eigen Cryo-EM Maps. However, the best structure match needs to be done in a separate floe. Caution: This floe can be expensive for large systems using 2D eigenmaps, even when the default settings are used (more than $1000 for systems with greater than 1000 residues).
Promoted Parameters
Title in user interface (promoted name)
Weighted Ensemble Parameters
Total Cumulative Number of Iterations (iterations): Desired number of iterations, including all previous simulations.
Required
Type: integer
Inputs
Collection (collection): Protein sampling data generated in the previous round of weighted ensemble MD simulation. Simulation data generated in this run will be added to this input collection.
Required
Type: collection_source
Default: wemd_simulation_collection
Outputs
Failure Report (fail_report): Output report to generate upon failure.
Type: string
Default: Protein Sampling Failure Report
Output Dataset (simulation_data_out): Output dataset to which to write.
Required
Type: dataset_out
Default: WESimulation_Dataset_Out
Reweighting Option
Reweighting (reweighting): Toggle on to periodically reweight trajectory walkers using WESS or WEED plugin (for non-equilibrium steady state or equilibrium sampling, respectively).
Type: boolean
Default: False
Choices: [True, False]
Number of Bins for Reweighting (reweighting_nbins): Number of bins for automatic reweighting. (use the JSON File Reweighting input to set reweighting bins manually)
Type: integer
Default: 10
Reweighting Period (reweighting_period): The period of reweighting the trajectory segments in terms of the number of iterations. No reweighting when set to 0. This parameter will be set to the value specified here when resuming a simulation.
Required
Type: integer
Default: 50
Reweighting Window Size (reweighting_window): The fraction of previous iterations used for estimating the transition rates for reweighting. This parameter will be set to the value specified here when resuming a simulation.
Required
Type: decimal
Default: 0.75
Report Settings
Floe Report (simulation_report_out): The title for the output floe report.
Required
Type: string
Default: Continue WEMD Simulation Report
Number of iterations for averaged distributions (average_window): Number of iterations to generate averaged density distributions for calculating the Kullback-Leibler divergence in each dimension.
Type: integer
Default: 2
Number of Bins for Histogram (n_bins): Number of bins for plotting the density distribution in each dimension.
Type: integer
Default: 50
Option for reference PDF (ref_type): Set type of reference probability distribution function for KL divergence.
Type: string
Default: Accumulated
Choices: [‘Accumulated’, ‘Averaged’]
Orion settings for cost optimization of WEMD simulation
Spot policy (spot_policy): Control cube placement on spot market instances
Type: string
Default: Required
Choices: [‘Allowed’, ‘Preferred’, ‘NotPreferred’, ‘Prohibited’, ‘Required’]
Instance Type (instance_type): The type of instance that this cube needs to be run on
Type: string
Maximum number of Parallel Cubes for MD (max_parallel): The maximum number of concurrently running copies of this Cube
Type: integer
Default: 1000